Analyzing Blending Social and Mass Media Audiences through the Lens of Computer-Mediated Discourse

Analyzing Blending Social and Mass Media Audiences through the Lens of Computer-Mediated Discourse

Asta Zelenkauskaite
ISBN13: 9781466661141|ISBN10: 1466661143|EISBN13: 9781466661158
DOI: 10.4018/978-1-4666-6114-1.ch067
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MLA

Zelenkauskaite, Asta. "Analyzing Blending Social and Mass Media Audiences through the Lens of Computer-Mediated Discourse." Digital Arts and Entertainment: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2014, pp. 1360-1382. https://doi.org/10.4018/978-1-4666-6114-1.ch067

APA

Zelenkauskaite, A. (2014). Analyzing Blending Social and Mass Media Audiences through the Lens of Computer-Mediated Discourse. In I. Management Association (Ed.), Digital Arts and Entertainment: Concepts, Methodologies, Tools, and Applications (pp. 1360-1382). IGI Global. https://doi.org/10.4018/978-1-4666-6114-1.ch067

Chicago

Zelenkauskaite, Asta. "Analyzing Blending Social and Mass Media Audiences through the Lens of Computer-Mediated Discourse." In Digital Arts and Entertainment: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1360-1382. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-6114-1.ch067

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Abstract

In recent years, mass media content has undergone a blending process with social media. Large amounts of text-based social media content have not only shaped mass media products, but also provided new opportunities to access audience behaviors through these large-scale datasets. Yet, evaluating a plethora of audience contents strikes one as methodologically challenging endeavor. This study illustrates advantages and applications of a mixed-method approach that includes quantitative computer-mediated discourse analysis (CMDA) and automated analysis of content frequency. To evaluate these methodologies, audience comments consisting of Facebook comments and SMS mobile texting to Italian radio-TV station RTL 102.5 were analyzed. Blended media contents through computer-mediated discourse analysis expand horizons for theoretical and methodological audience analysis research in parallel to established audience analysis metrics.

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